This exam has no name on it! And your username on here also has no identifiable name in it, so I can't give you a grade! Just email me and say this is your midterm, all right? Any grade is better than no grade! This isn't my responsibility; if you can't put your name on something then I just can't give you credit for it.
Background:
While none of the data gathered relates directly to urban and rural cleavages, everything still creates a picture of the opinions of voters in the 2008 election in regards to economic classes. I was mostly interested in the working class, poor people and big business, which is why I generated summaries for their statistical information. I was able to piece together some descriptive statistics regarding the voters opinion on various classes in society, which to me is very interesting. This dataset enabled us to develop a general idea of the view of the voters.
-This first box plot compares the public's opinion of big business and poor people. This second box plot is comparing the feelings toward big business again however comparing them to the working class. These plots show the relationship between the way people feel towards various 'classes'. People appear to be more in favor of the working class over big business.
-There appears to be a relationship between the amount of people that liked big business and the amount of people that were in favor of poor people. The higher approval is for big business, people either are in favor of the poor or not, not much middle ground. This seems like something people have very strong opinions about.
-Here is another scatterplot that shows a slight positive correlation between opinions of big business and the working class. It maintains a somewhat paralel at a rate of 0.1970637
/\ (is actually another boxplot I saved it with the wrong name and I couldn't figure out how to change the file name)
-I made a histogram to compare big business to the working class.
Copy of script:
nes<-read.csv("anes2008.csv") > summary(nes$workclass)
Min. 1st Qu. Median Mean 3rd Qu. Max. NA's
1.00 70.00 85.00 83.97 100.00 100.00 236 > summary(nes$bigbiz)
Min. 1st Qu. Median Mean 3rd Qu. Max. NA's
0.00 40.00 50.00 55.27 70.00 100.00 259 > summary(nes$workclass)
Min. 1st Qu. Median Mean 3rd Qu. Max. NA's
1.00 70.00 85.00 83.97 100.00 100.00 236 > summary(nes$poorppl)
Min. 1st Qu. Median Mean 3rd Qu. Max. NA's
0.00 60.00 70.00 74.55 96.25 100.00 266 > summary(nes$richppl)
Min. 1st Qu. Median Mean 3rd Qu. Max. NA's
0.00 50.00 50.00 58.28 70.00 100.00 279 > hist(nes$bigbiz) > sd(nes$poorppl, na.rm=TRUE)
[1] 19.74461 > boxplot(nes$bigbiz ~ nes$workclass)
The downloaded binary packages are in
/var/folders/tf/jtwl6nhs7dq_9hyfs9ykysp40000gn/T//Rtmp7LaDsu/downloaded_packages > library(car)
Loading required package: MASS
Loading required package: nnet
Attaching package: ‘car’
The following object(s) are masked from ‘package:Hmisc’:
So basically, you were unable to figure out the data management. All right, well you had plenty of time before, after, and during the exam period, to ask me or other students for help! There's hardly anything here, other than errors and just a few unexplained summary statistics. Come see me and we'll work double time to get you caught up to speed, all right?
Marisa J. Bennett
This exam has no name on it! And your username on here also has no identifiable name in it, so I can't give you a grade! Just email me and say this is your midterm, all right? Any grade is better than no grade! This isn't my responsibility; if you can't put your name on something then I just can't give you credit for it.
Background:
While none of the data gathered relates directly to urban and rural cleavages, everything still creates a picture of the opinions of voters in the 2008 election in regards to economic classes. I was mostly interested in the working class, poor people and big business, which is why I generated summaries for their statistical information. I was able to piece together some descriptive statistics regarding the voters opinion on various classes in society, which to me is very interesting. This dataset enabled us to develop a general idea of the view of the voters.
-This first box plot compares the public's opinion of big business and poor people. This second box plot is comparing the feelings toward big business again however comparing them to the working class. These plots show the relationship between the way people feel towards various 'classes'. People appear to be more in favor of the working class over big business.
bigbiz v poor scatterplot.pdf
- Details
- Download
- 189 KB
-There appears to be a relationship between the amount of people that liked big business and the amount of people that were in favor of poor people. The higher approval is for big business, people either are in favor of the poor or not, not much middle ground. This seems like something people have very strong opinions about.-Here is another scatterplot that shows a slight positive correlation between opinions of big business and the working class. It maintains a somewhat paralel at a rate of 0.1970637
/\ (is actually another boxplot I saved it with the wrong name and I couldn't figure out how to change the file name)
-I made a histogram to compare big business to the working class.
Copy of script:
nes<-read.csv("anes2008.csv")
> summary(nes$workclass)
Min. 1st Qu. Median Mean 3rd Qu. Max. NA's
1.00 70.00 85.00 83.97 100.00 100.00 236
> summary(nes$bigbiz)
Min. 1st Qu. Median Mean 3rd Qu. Max. NA's
0.00 40.00 50.00 55.27 70.00 100.00 259
> summary(nes$workclass)
Min. 1st Qu. Median Mean 3rd Qu. Max. NA's
1.00 70.00 85.00 83.97 100.00 100.00 236
> summary(nes$poorppl)
Min. 1st Qu. Median Mean 3rd Qu. Max. NA's
0.00 60.00 70.00 74.55 96.25 100.00 266
> summary(nes$richppl)
Min. 1st Qu. Median Mean 3rd Qu. Max. NA's
0.00 50.00 50.00 58.28 70.00 100.00 279
> hist(nes$bigbiz)
> sd(nes$poorppl, na.rm=TRUE)
[1] 19.74461
> boxplot(nes$bigbiz ~ nes$workclass)
- cor(nes$bigbiz, nes$workclass, use="complete.obs")
[1] 0.1970637> boxplot(nes$bigbiz ~ nes$poorppl)
> install.packages("car")
trying URL 'http://lib.stat.cmu.edu/R/CRAN/bin/macosx/leopard/contrib/2.15/car_2.0-15.tgz'
Content type 'application/x-gzip' length 1064620 bytes (1.0 Mb)
opened URL
======================================
downloaded 1.0 MbThe downloaded binary packages are in
/var/folders/tf/jtwl6nhs7dq_9hyfs9ykysp40000gn/T//Rtmp7LaDsu/downloaded_packages
> library(car)
Loading required package: MASS
Loading required package: nnet
Attaching package: ‘car’
The following object(s) are masked from ‘package:Hmisc’:
recode
> scatterplot(nes$bigbiz, nes$workclass)
- scatterplot(nes$bigbiz, nes$poorppl)
> plot(density(nes$bigbiz, na.rm = TRUE))> plot(density(nes$workclass, na.rm = TRUE))
So basically, you were unable to figure out the data management. All right, well you had plenty of time before, after, and during the exam period, to ask me or other students for help! There's hardly anything here, other than errors and just a few unexplained summary statistics. Come see me and we'll work double time to get you caught up to speed, all right?